{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import some libraries, set parameters, and load text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import gensim # vectorization library\n",
    "from gensim import corpora\n",
    "from sklearn.manifold import TSNE\n",
    "import re\n",
    "from nltk.corpus import stopwords\n",
    "import numpy as np\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#parameters\n",
    "MIN = 5\n",
    "METHOD = 'CBOW'\n",
    "STOPWORDS = True\n",
    "SIZE = 10000\n",
    "DIM = 768 # same as transformer\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('../data/reddit_batch1/batch.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "####random shuffle and truncate until 'size' sentences"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "#df = df.sample(frac=1).reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.iloc[0:SIZE]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "data: batch from reddit "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "nn = df['topic'].unique().shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "stop_words = set(stopwords.words('english'))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "#removes blanks, stopwords and non alphanumeric\n",
    "def clean_sen(sent):\n",
    "    if STOPWORDS == True:\n",
    "        clean_list = [word.lower() for word in sent.split() if word not in stop_words]\n",
    "    else:\n",
    "        clean_list = [word.lower() for word in sent.split()]\n",
    "    #clean_list = [re.sub('[^A-Za-z]','',word) for word in clean_list]\n",
    "    clean_list = [re.sub('[\\W_]+','',word) for word in clean_list]\n",
    "    clean_list = [re.sub(' +', ' ', word) for word in clean_list]\n",
    " \n",
    "    return clean_list\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "pre1= []\n",
    "for i in df.sentence:\n",
    "    clean = clean_sen(i)\n",
    "    if len(clean) > MIN:\n",
    "        pre1.append(clean)\n",
    "       \n",
    "    \n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Word2vec "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "from gensim.models import Word2Vec\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = Word2Vec(size=DIM,min_count=MIN,sg=0) if METHOD == 'CBOW' else Word2Vec(size=DIM,min_count=MIN,sg=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.build_vocab(sentences=pre1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(8434331, 9889700)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.train(pre1,epochs=50,total_examples=model.corpus_count)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "vecs = model.wv"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Function to random sample n words from dictionary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "#nn=15\n",
    "top=15"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "def sample(vecs,nn,top):\n",
    "    words_cl = []\n",
    "    emb_cl = []\n",
    "    voc = vecs.index2word\n",
    "    for i in range(nn):        \n",
    "        pre_words_cl=[]\n",
    "        pre_emb_cl =[]\n",
    "        choice = np.random.randint(0,len(voc))\n",
    "        w = voc[choice]\n",
    "        simil = vecs.most_similar(w,topn=top)\n",
    "        for sim in simil:\n",
    "            \n",
    "            pre_words_cl.append(sim[0])\n",
    "            pre_emb_cl.append(vecs[sim[0]])\n",
    "        words_cl.append(pre_words_cl)\n",
    "        emb_cl.append(pre_emb_cl)\n",
    "    return words_cl, emb_cl\n",
    "\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "words_cl,emb_cl = sample(vecs,nn,top)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### function to plot tsne"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.cm as cm\n",
    "%matplotlib inline\n",
    "\n",
    "def plotsne(words,embs,perp):\n",
    "    \n",
    "    embs1 = np.array(embs).reshape(nn*top,DIM) ### reshape to nrandom*topn,DIM\n",
    "    tsne_2d = TSNE(perplexity=perp, n_components=2, init='pca', n_iter=3500, random_state=32)\n",
    "    emb_2d = np.array(tsne_2d.fit_transform(np.array(embs1)))    \n",
    "    \n",
    "    plt.figure(figsize=(16, 9))\n",
    "    space = np.expand_dims(np.linspace(0,1,nn),axis=1)\n",
    "    colors = cm.rainbow(space)\n",
    "    \n",
    "    \n",
    "    j = 0\n",
    "    jj = 0\n",
    "    for clust in words:\n",
    "        \n",
    "        for i in clust:\n",
    "\n",
    "            plt.annotate(i,xy=(emb_2d[j][0],emb_2d[j][1]),size=8,alpha=0.5)\n",
    "       \n",
    "            plt.scatter(emb_2d[j,0],emb_2d[j,1],alpha=0.8,c=colors[jj])\n",
    "            j+=1\n",
    "        jj += 1\n",
    "    plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotsne(words_cl,emb_cl,10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
